The above probability distribution has a close analogue among centrality indices studied in network science.
Various centrality indices have been proposed in network theory to quantify which nodes in a graph are, in a suitably
defined sense, most important [1]}. With uniform prior \(p_\alpha = N_{\rm dS}^{-1}\)  over ancestral vacua, (REF )
is similar to the Katz centrality measure [2]} on a graph:
\(\vec{C}_{\rm Katz} = \left( \left({1} - \alpha A^\intercal \right)^{-1} - {1} \right)\vec{e}\,,\) 
